On the least squares estimator in a nearly unstable sequence of stationary spatial AR models

A nearly unstable sequence of stationary spatial autoregressive processes is investigated, when the sum of the absolute values of the autoregressive coefficients tends to one. It is shown that after an appropriate normalization the least squares estimator for these coefficients has a normal limit distribution. If none of the parameters equals zero then the typical rate of convergence is n.

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Year of publication:	2009
Authors:	Baran, Sándor ; Pap, Gyula
Published in:	Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 100.2009, 4, p. 686-698
Publisher:	Elsevier
Subject:	primary \| 62M10 secondary \| 62F12 Autoregressive model Asymptotic normality Martingale central limit theorem

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005093858